Changes in supramolecular organization of cyanobacterial thylakoid membrane complexes in response to far-red light photoacclimation

Cyanobacteria are ubiquitous in nature and have developed numerous strategies that allow them to live in a diverse range of environments. Certain cyanobacteria synthesize chlorophylls d and f to acclimate to niches enriched in far-red light (FRL) and incorporate paralogous photosynthetic proteins into their photosynthetic apparatus in a process called FRL-induced photoacclimation (FaRLiP). We characterized the macromolecular changes involved in FRL-driven photosynthesis and used atomic force microscopy to examine the supramolecular organization of photosystem I associated with FaRLiP in three cyanobacterial species. Mass spectrometry showed the changes in the proteome of Chroococcidiopsis thermalis PCC 7203 that accompany FaRLiP. Fluorescence lifetime imaging microscopy and electron microscopy reveal an altered cellular distribution of photosystem complexes and illustrate the cell-to-cell variability of the FaRLiP response.

Scale bar is 100 nm.. (B) Sucrose density gradients of solubilised membranes from WL (left) and FRL (right) cells in which green bands can be observed that correspond to different oligomeric states of photosynthetic complexes. The black rectangle highlights the green band that corresponds to trimeric PSI in WL membranes. The red rectangle highlights the major band in the density gradient, which corresponds to PSI trimers, and suggests an increased proportion of trimeric PSI complexes in FRLacclimated membranes.

Fig. S4. Correlation matrices for three technical replicate proteomic analyses of thylakoid membranes from C. thermalis cells acclimated under (A) WL and (B) FRL.
Thylakoid membranes were subjected to quantitative proteomic analysis in triplicate as described in Materials and Methods, with protein abundance scores calculated by the iBAQ method and normalized to the intra-analysis sum of iBAQ abundance scores. The numbers of protein identifications for each replicate are shown in red and the Spearman rank correlation coefficients in blue. A total of 629 proteins were quantified and the data-points are listed in Supplementary Data S1.

Fig. S5 Alignment of PsaA and PsaB homologs showing the location of shared tryptic peptides.
Proteomic analysis most often employs upstream proteolysis with trypsin to generate peptide fragments for nano-flow liquid chromatography coupled on-line to mass spectrometry. Protein homologs with a significant degree of sequence identity may contain shared tryptic peptides. This situation is exemplified by isoforms of the photosystem I subunits (A) Chro_5026/1019 (PsaA1/A2) and (B) Chro_5027/1018 (PsaB1/B2), with shared peptides highlighted in colored rectangles. For quantification of differential expression by iBAQ, which utilizes the sum of all peptide ion intensities attributable to each protein, peptides with ion intensities contributed by more than one isoform may introduce inaccuracy. For relative quantification of photosystem subunit isoforms, we instead used the Top-N method in which the three most intense and unique tryptic peptide ion intensities mapping to a protein were summed to generate the abundance score.

Data S1. (separate file)
This data set is from Chroococcidiopsis thermalis PCC7203 cells were acclimated under white and far-red light illumination. Proteins were extracted from thylakoid membranes and digested with endoproteinase Lys-C and trypsin. The resultant peptide fragments were analysed by nanoLC-MS/MS as three technical repeats (Rep 1, 2, 3) and the mass spectra subjected to database searching by MaxQuant as described in Materials and Methods.
Protein abundance scores were derived by the iBAQ (intensity-based absolute quantification) method, as implemented by MaxQuant. These values were normalized using Perseus to the intra-analysis sum of iBAQ scores to compensate for random variability arising from sample loading and MS full-scan/product ion scan data-dependent acquisition patterns. The normalized abundance scores were then transformed to log(2). Missing values resulting from the non-detection of proteins in some analyses were replaced by imputation of random values (shown in blue) derived from a normal distribution and weighted to simulate expected low abundance scores, as implemented in Perseus using the default parameters.
Statistical analysis in Perseus was by a modified t-test to provide the significance threshold at p < 0.05. The -log(10) p-values and differences (FRL -WL iBAQ score averages) provide the data-points for the volcano plots in Fig. 4A, C (main article).

Data S2. (separate file)
This Data Set is derived from the same MaxQuant output as Data S1 and is confined to the photosystem subunits that were identified and quantified in both white and far-red light thylakoid protein extracts.
Abundance scores were derived by the Top-N method using tryptic peptide ion intensity values calculated by MaxQuant. These values were normalized using Perseus to the intra-analysis sum of peptide ion intensities to compensate for the random variability arising as described above. Each protein abundance score was determined by summing the normalized intensity values for the 1, 2 or 3 most intense peptide ions, depending on the number of peptides identified.
After transformation of the summed intensity values to log(2), statistical analysis was carried out as described above with the -log(10) p-values and differences (FRL -WL Top-N score averages) used to provide the data-points for the volcano plot in Fig. 4B (main article).